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Global Positioning System (GPS) technology has revolutionized navigation and positioning, but its accuracy is often compromised by various errors. These errors, stemming from environmental, satellite, and receiver-related factors, require careful mitigation to ensure reliable performance across applications.Atmospheric ErrorsGPS signals travel through the Earth’s ionosphere and troposphere, introducing delays which affect accuracy. The ionosphere is strongly influenced by charged particles,...
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Surveyors use Global Positioning System (GPS) technology to measure the precise location and elevation of points on Earth. In a recent survey, GPS receivers were used to determine the coordinates and elevations of two park monuments. The process involved careful mission planning, data collection, and correction to ensure accuracy. The survey began with mission planning to identify optimal satellite visibility and minimize Position Dilution of Precision (PDOP). A geodetic control point...
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A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
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The Global Positioning System (GPS) revolutionized positioning on Earth, providing precise location data through satellite ranging. The GPS system was developed in 1978 by the U.S. Department of Defense  for military use, and it became available for civilian applications in 1983, transforming fields including navigation, fleet management, and time synchronization for telecommunications systems.GPS consists of satellites in medium Earth orbit, about 20,200 kilometers above the surface,...
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A Dead Reckoning Calibration Scheme Based on Optimization with an Adaptive Quantum-Inspired Evolutionary Algorithm

Biao Yu1, Hui Zhu1, Deyi Xue2

  • 1Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China.

Entropy (Basel, Switzerland)
|August 26, 2022
PubMed
Summary
This summary is machine-generated.

Accurate self-localization is vital for intelligent vehicles. This study introduces an optimization method using differential global positioning system (DGPS) data to calibrate dead reckoning parameters, overcoming challenges with traditional path-dependent methods.

Keywords:
adaptive quantum-inspired evolutionary algorithmdead reckoningintelligent vehicleoptimizationparameter calibration

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Area of Science:

  • Robotics and Control Systems
  • Autonomous Vehicle Navigation
  • Computational Intelligence

Background:

  • Self-localization via dead reckoning is crucial for intelligent vehicle control, including autonomous driving.
  • Traditional dead reckoning calibration methods require specialized paths, which are impractical for complex real-world road conditions.
  • Existing methods face limitations in accurately calibrating dead reckoning parameters for intelligent vehicles in dynamic environments.

Purpose of the Study:

  • To develop a novel, optimization-based dead reckoning calibration scheme for intelligent vehicles.
  • To address the impracticality of path-dependent calibration methods in complex driving scenarios.
  • To enhance the accuracy and efficiency of self-localization in autonomous systems.

Main Methods:

  • An optimization-based calibration scheme was proposed, utilizing differential global positioning system (DGPS) for precise vehicle positioning.
  • The objective function was defined as minimizing the positional error between dead reckoning and DGPS measurements.
  • An adaptive quantum-inspired evolutionary algorithm (AQIEA) was developed to optimize the calibration parameters.

Main Results:

  • The proposed scheme effectively calibrated dead reckoning parameters for intelligent vehicles, demonstrating high accuracy.
  • The AQIEA showed improved optimization quality and efficiency compared to classic genetic algorithms and standard quantum-inspired evolutionary algorithms.
  • Experimental validation confirmed the practical effectiveness of the developed calibration scheme in real-world intelligent vehicle applications.

Conclusions:

  • The developed optimization-based dead reckoning calibration scheme offers a viable solution for intelligent vehicles, overcoming limitations of traditional methods.
  • The adaptive quantum-inspired evolutionary algorithm presents a superior approach for parameter optimization in this context.
  • This research contributes to more reliable and accurate self-localization in autonomous driving systems.